ARTIFICIAL INTELLIGENCE ENGINEERING
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
AIN2008	Computers and Ethics	Spring	2	0	2	5

Basic information

Language of instruction:	English
Type of course:	Must Course
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Face to face
Course Coordinator :	Assist. Prof. FATİH KAHRAMAN
Recommended Optional Program Components:	-
Course Objectives:	This course aims to provide technical and non-technical information for candidates who will be AI engineers.

Learning Outcomes

The students who have succeeded in this course;
- Identifies and analyzes the ethical, legal, and social impacts of information technologies.
- Explains and evaluates fundamental ethical theories, principles, and frameworks related to computer ethics.
- Understands digital privacy, data protection, and security risks and makes ethical decisions accordingly.
- Develops awareness of software licensing, copyrights, patents, and open-source software.
- Applies ethical principles in digital environments and recognizes unethical online behaviors.
- Explains ethical responsibilities and professional standards for computing professionals.
- Understands cybercrimes, cyberbullying, and unethical digital activities and evaluates strategies to combat them.
- Analyzes the ethical dimensions of artificial intelligence, automation, and algorithmic decision-making.
- Assesses the impact of information technologies on society, economy, and culture.
- Evaluates ethical dilemmas in the field of computing and applies critical thinking in ethical decision-making processes.

Course Content

This course deals with the use of data and other technologies developed with the introduction of the internet into our lives, both in social life and in the business environment, in accordance with ethical norms. The teaching methods of the course include lectures, group work, guest/expert invitations, reading, project preparation, and project development.

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Introduction and Defining the Field of Computer Ethics
2)	Perspectives on Artificial Intelligence
3)	Concepts of AI Ethics
4)	Technical Recommendations on the Ethics of AI
5)	Ethical Principles, Benefits, and Issues of AI
6)	Data Privacy-Preserving Techniques
7)	Legal Aspects of IoT
8)	Cybersecurity Cases on Global Perspectives
9)	AI Ethics Stakeholders and Ethical Digital Ecosystem
10)	Human Rights and AI
11)	AI Ethics & Consequences
12)	Blockchain and Ethical Perspective
13)	Responsible Use of AI in Digital Organizations
14)	Metaverse and Gaming Technologies by Ethical Perspective

Sources

Course Notes / Textbooks:

Bernd Carsten Stahl, "Artificial Intelligence for a Better Future: An Ecosystem Perspective on the Ethics of AI and Emerging Digital Technologies”, Springer, ISBN-978-3-030-69978-9, 2020.

European Commission, “Ethics Guidelines for Trustworthy AI”, https://ec.europa.eu/futurium/en/ai-alliance-consultation.1.html

Gry Hasselbalch, “Data Ethics of Power: A Human Approach in the Big Data and AI Era”, Edward Elgar Publishing, ISBN: 978 1 80220 310 3, 2021.

References:

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Attendance	14	% 15
Presentation	1	% 45
Midterms	1	% 30
Final	1	% 10
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 90
PERCENTAGE OF FINAL WORK		% 10
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	3	42
Presentations / Seminar	1	40	40
Midterms	1	30	30
Final	1	20	20
Total Workload			132

Contribution of Learning Outcomes to Programme Outcomes

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Build up a body of knowledge in mathematics, science and Artificial Intelligence Engineering subjects; use theoretical and applied information in these areas to model and solve complex engineering problems.
2)	Design complex Artificial Intelligence systems, platforms, processes, devices or products under realistic constraints and conditions, in such a way as to meet the desired result; apply modern design methods for this purpose.
3)	Identify, formulate, and solve complex Artificial Intelligence Engineering problems; select and apply proper modeling and analysis methods for this purpose.
4)	Devise, select, and use modern techniques and tools needed for solving complex problems in Artificial Intelligence Engineering practice; employ information technologies effectively.
5)	Design and conduct numerical or physical experiments, collect data, analyze and interpret results for investigating the complex problems specific to Artificial Intelligence Engineering.
6)	Ability to communicate effectively in English and Turkish (if he/she is a Turkish citizen), both orally and in writing. Write and understand reports, prepare design and production reports, deliver effective presentations, give and receive clear and understandable instructions.
7)	Recognize the need for life-long learning; show ability to access information, to follow developments in science and technology, and to continuously educate oneself.
8)	Develop an awareness of professional and ethical responsibility, and behave accordingly. Be informed about the standards used in Artificial Intelligence Engineering applications.	4
9)	Learn about business life practices such as project management, risk management, and change management; develop an awareness of entrepreneurship, innovation, and sustainable development.	4
10)	Acquire knowledge about the effects of practices of Artificial Intelligence Engineering on health, environment, security in universal and social scope, and the contemporary problems of Artificial Intelligence Engineering; is aware of the legal consequences of Mechatronics engineering solutions.	5
11)	Cooperate efficiently in intra-disciplinary and multi-disciplinary teams; and show self-reliance when working on Artificial Intelligence-related problems.	4